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Abstract We put forward a new data object called the public transit travel time cube and demonstrate how the cube can be used in the analysis of transit travel time changes over space and time. The travel time cube contains the shortest path transit travel time between sets of origins and destinations in the city, at all times of day. Once computed, a wide range of investigations become readily available to the transit planner or transportation researcher. We conduct three demonstrative analyses using travel time cubes for the Wasatch Front, Utah and the Portland region in Oregon. Our studies investigate how travel times were impacted by service cuts and expansions in the two regions respectively and the impact this had on jobs accessibility. We also use the travel time cube to study the last mile problem, and compute the travel time savings and the stability gained by solving the last mile problem with bicycling. The paper concludes with an expanded discussion on the merits of the travel time cube and outlines four avenues for continued research.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 119 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
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